As a machine learning engineer, understanding large language models (LLMs) is crucial for creating accurate and transparent AI systems. However, diving into LLMs can be overwhelming due to the vast amount of complex information available.
Fortunately, there are five free books that cover various aspects of LLMs, including theory, linguistics, systems, interpretability, and security. These resources will provide a solid foundation for anyone serious about learning large language models.
The first book, “Foundations of Large Language Models,” is an excellent resource for understanding the core mechanisms behind modern models like GPT, BERT, and LLaMA. The authors, Tong Xiao and Jingbo Zhu, provide a clear and concise explanation of pre-training, generative models, prompting, alignment, inference, and more.
The second book, “Speech and Language Processing,” by Daniel Jurafsky and James H. Martin, is a comprehensive resource for understanding NLP and LLMs. The book covers modern NLP topics, including Transformers, LLMs, automatic speech recognition, and text-to-speech systems.
For those interested in the practical aspects of training LLMs on TPUs, “How to Scale Your Model: A Systems View of LLMs on TPUs” is an excellent resource. The authors, who have worked on production-grade LLM systems at Google, provide a detailed explanation of parallelism strategies for both training and inference.
The fourth book, “Understanding Large Language Models: Towards Rigorous and Targeted Interpretability Using Probing Classifiers and Self-Rationalisation,” explores the unique aspect of LLMs through probing classifiers and self-rationalization. This thesis provides valuable insights into how to better understand large language models and create more transparent AI systems.
Lastly, “Large Language Models in Cybersecurity: Threats, Exposure and Mitigation” is a unique resource that focuses on the security aspects of LLMs. The book covers risks such as private information leakage, phishing attacks, and vulnerabilities from code suggestions, providing valuable insights into how to mitigate these threats.
These five books provide an excellent starting point for anyone serious about learning large language models. With their diverse range of topics and expert authors, they form a comprehensive learning path that will help you develop a deep understanding of LLMs.
Source: https://www.kdnuggets.com/the-5-free-must-read-books-for-every-llm-engineer